Merge branch 'next' into outputRefactoring

22 files changed, 211 insertions, 456 deletions

diff --git a/dpd/README.md b/dpd/README.md
index 24611d9..fc84bad 100644
--- a/dpd/README.md
+++ b/dpd/README.md
@@ -81,50 +81,66 @@ essential that there is no nonlinearity in the RX path!
 Software Setup
 --------------
 
-We assume that you already installed *ODR-DabMux* and *ODR-DabMod*. In order to
-satisfy dependencies for the predistortion, you can install all required python
-modules using *conda*. To obtain the *conda* command line tool, install
-[miniconda](https://conda.io/docs/user-guide/install/linux.html) and do the
-beginners tutorial. It helps you keep the global python environment clean and
-install the exact same package versions as we used for development.
-
-```
-conda env create -f dpd/environment.yml
-source activate dab
-```
-
-Alternatively you can also install the dependencies from your distribution.
-You will need at least scipy, matplotlib and python-zeromq, and maybe more.
-
+We assume that you already installed *ODR-DabMux* and *ODR-DabMod*.
+You should install the required python dependencies for the DPDCE using
+distribution packages. You will need at least scipy, matplotlib and
+python-zeromq.
 
 Use the predistortion
 ----------------------
 
-Run the multiplexer and the modulator:
+Make sure you have a ODR-DabMux running with a TCP output on port 9200.
+
+Then run the modulator, with the example dpd configuration file.
 
 ```
-ODR-DabMux/src/odr-dabmux ../simple.mux
-ODR-DabMod/odr-dabmod dpd/dpd.ini
+./odr-dabmod dpd/dpd.ini
 ```
 
+This configuration file is different from usual defaults in several respects:
+
+ * logging to /tmp/dabmod.log
+ * 4x oversampling: 8192000 sample rate
+ * a very small digital gain, which will be overridden by the DPDCE
+ * predistorter enabled
+ * UHD output with a rather low TX gain, which will be overridden by DPDCE
+
 The DPDCE uses automatic gain control for both TX and RX gain to get both a
 high quantisation quality for the most frequent amplitude regions and a high
 enough back-off so the peaks are also quantised correctly. This means that the
 output power will stay at the same level, but the DPDCE may change TX gain to
-trade it with digital gain and also change RX gain.
-
-As a first test you should run the DPDCE with the *--plot* parameter. It
-preserves the output power and generates all available visualisation plots in
-the newly created logging directory `/tmp/dpd_<time_stamp>`. As the predistortion
-should increase the peak to shoulder ratio, you should select a *txgain* in the
-ODR-DabMod configuration file such that the initial peak-to-soulder ratio
-visible on your spectrum analyser. This way, you will be able to see a the
+trade it with digital gain and also change RX gain. This also implies that you
+should *not modify txgain, rxgain, digital gain or coefficient settings manually!*
+When the DPDCE is used, it controls these settings, and there are command line
+options for you to define initial values.
+
+To verify that the communication between the DPDCE and ODR-DabMod is ok,
+you can use the status and reset options:
+
+```
+cd dpd
+python main.py --status
+python main.py --reset
+```
+
+The reset option sets all DPD-related settings to the defaults (as shown in the
+`--help` usage screen) and stops.
+
+When neither `--status` nor `--reset` is given, the DPDCE will run the predistortion
+algorithm. As a first test you should run the DPDCE with the `--plot`
+parameter. It preserves the output power and generates all available
+visualisation plots in the newly created logging directory
+`/tmp/dpd_<time_stamp>`. As the predistortion should increase the peak to
+shoulder ratio, you should select a *txgain* in the ODR-DabMod configuration
+file such that the initial peak-to-soulder ratio visible on your spectrum
+analyser. This way, you will be able to see a the
 change.
 
 ```
 cd dpd
 python main.py --plot
 ```
+
 The DPDCE now does 10 iterations, and tries to improve the predistortion effectiveness.
 In each step the learning rate is decreased. The learning rate is the factor
 with which new coefficients are weighted in a weighted mean with the old
@@ -137,7 +153,8 @@ time stamp and its label. Following plots are generated chronologically:
  - ExtractStatistic: Extracted information from one or multiple measurements.
  - Model\_AM: Fitted function for the amplitudes of the power amplifier against the TX amplitude.
  - Model\_PM: Fitted function for the phase difference of the power amplifier against the TX amplitude.
- - adapt.pkl: Contains the settings for the predistortion. To load them again without further measurements, you can use `apply_adapt_dumps.py`.
+ - adapt.pkl: Contains all settings for the predistortion.
+   You can load them again without doing measurements with the `apply_adapt_dumps.py` script.
  - MER: Constellation diagram used to calculate the modulation error rate.
 
 After the run you should be able to observe that the peak-to-shoulder
@@ -198,7 +215,7 @@ TODO
    same.
  - At the moment we assume that the USRP RX gain has to be larger than 30dB and
    the received signal should have a median absolute value of 0.05 in order to
-   have a hight quality quantization. Do measurements to support or improve
+   have a high quality quantization. Do measurements to support or improve
    this heuristic.
  - Check if we need to measure MER differently (average over more symbols?)
  - Is -45dBm the best RX feedback power level?
diff --git a/dpd/apply_adapt_dumps.py b/dpd/apply_adapt_dumps.py
index 6b15aff..20bc013 100755
--- a/dpd/apply_adapt_dumps.py
+++ b/dpd/apply_adapt_dumps.py
@@ -6,173 +6,50 @@
 # http://www.opendigitalradio.org
 # Licence: The MIT License, see notice at the end of this file
 
-"""This Python script is the main file for ODR-DabMod's DPD Computation Engine.
-This engine calculates and updates the parameter of the digital
-predistortion module of ODR-DabMod."""
-
 import datetime
 import os
-import matplotlib
 import glob
-import natsort
-matplotlib.use('GTKAgg')
-
 import logging
 
 dt = datetime.datetime.now().isoformat()
-logging_path = "/tmp/dpd_{}".format(dt).replace(".", "_").replace(":", "-")
-os.makedirs(logging_path)
 logging.basicConfig(format='%(asctime)s - %(module)s - %(levelname)s - %(message)s',
                     datefmt='%Y-%m-%d %H:%M:%S',
-                    filename='{}/dpd.log'.format(logging_path),
-                    filemode='w',
                     level=logging.DEBUG)
 
-# also log up to INFO to console
-console = logging.StreamHandler()
-console.setLevel(logging.INFO)
-# set a format which is simpler for console use
-formatter = logging.Formatter('%(asctime)s - %(module)s - %(levelname)s - %(message)s')
-# tell the handler to use this format
-console.setFormatter(formatter)
-# add the handler to the root logger
-logging.getLogger('').addHandler(console)
-
-import src.Measure as Measure
-import src.Model as Model
-import src.ExtractStatistic as ExtractStatistic
 import src.Adapt as Adapt
-import src.RX_Agc as Agc
-import src.TX_Agc as TX_Agc
 import argparse
 
-import src.Const
-import src.Symbol_align
-import src.Measure_Shoulders
-import src.MER
-
 parser = argparse.ArgumentParser(
-    description="DPD Computation Engine for ODR-DabMod")
+        description="Load pkl dumps DPD settings into ODR-DabMod")
 parser.add_argument('--port', default=50055, type=int,
                     help='port of DPD server to connect to (default: 50055)',
                     required=False)
 parser.add_argument('--rc-port', default=9400, type=int,
                     help='port of ODR-DabMod ZMQ Remote Control to connect to (default: 9400)',
                     required=False)
-parser.add_argument('--samplerate', default=8192000, type=int,
-                    help='Sample rate',
-                    required=False)
-parser.add_argument('--coefs', default='/tmp/poly.coef',
+parser.add_argument('--coefs', default='poly.coef',
                     help='File with DPD coefficients, which will be read by ODR-DabMod',
                     required=False)
-parser.add_argument('--txgain', default=75,
-                    help='TX Gain',
-                    required=False,
-                    type=int)
-parser.add_argument('--rxgain', default=30,
-                    help='TX Gain',
-                    required=False,
-                    type=int)
-parser.add_argument('--digital_gain', default=1,
-                    help='Digital Gain',
-                    required=False,
-                    type=float)
-parser.add_argument('--samps', default='81920', type=int,
-                    help='Number of samples to request from ODR-DabMod',
-                    required=False)
-parser.add_argument('--target_median', default=0.1,
-                    help='target_median',
-                    required=False,
-                    type=float)
-parser.add_argument('--searchpath', default='./stored', type=str,
-                    help='Path to search .pkl files with stored configuration'
-                         'for adapt',
-                    required=False)
-parser.add_argument('-L', '--lut',
-                    help='Use lookup table instead of polynomial predistorter',
-                    action="store_true")
+parser.add_argument('file', help='File to read the DPD settings from')
 
 cli_args = parser.parse_args()
 
 port = cli_args.port
 port_rc = cli_args.rc_port
 coef_path = cli_args.coefs
-digital_gain = cli_args.digital_gain
-txgain = cli_args.txgain
-rxgain = cli_args.rxgain
-num_req = cli_args.samps
-samplerate = cli_args.samplerate
-searchpath = cli_args.searchpath
-target_median = cli_args.target_median
-
-c = src.Const.Const(samplerate, target_median, False)
-SA = src.Symbol_align.Symbol_align(c)
-MER = src.MER.MER(c)
-MS = src.Measure_Shoulders.Measure_Shoulders(c)
-
-meas = Measure.Measure(samplerate, port, num_req)
-extStat = ExtractStatistic.ExtractStatistic(c)
-adapt = Adapt.Adapt(port_rc, coef_path)
-dpddata = adapt.get_predistorter
-
-if cli_args.lut:
-    model = Model.Lut(c)
-else:
-    model = Model.Poly(c)
-adapt.set_predistorter(model.get_dpd_data())
-adapt.set_digital_gain(digital_gain)
-adapt.set_txgain(txgain)
-adapt.set_rxgain(rxgain)
-
-tx_gain = adapt.get_txgain()
-rx_gain = adapt.get_rxgain()
-digital_gain = adapt.get_digital_gain()
-
-dpddata = adapt.get_predistorter()
-if dpddata[0] == "poly":
-    coefs_am = dpddata[1]
-    coefs_pm = dpddata[2]
-    logging.info(
-        "TX gain {}, RX gain {}, dpd_coefs_am {},"
-        " dpd_coefs_pm {}, digital_gain {}".format(
-            tx_gain, rx_gain, coefs_am, coefs_pm, digital_gain
-        )
-    )
-elif dpddata[0] == "lut":
-    scalefactor = dpddata[1]
-    lut = dpddata[2]
-    logging.info(
-        "TX gain {}, RX gain {}, LUT scalefactor {},"
-        " LUT {}, digital_gain {}".format(
-            tx_gain, rx_gain, scalefactor, lut, digital_gain
-        )
-    )
-else:
-    logging.error("Unknown dpd data format {}".format(dpddata[0]))
-
-tx_agc = TX_Agc.TX_Agc(adapt, c)
-
-# Automatic Gain Control
-agc = Agc.Agc(meas, adapt, c)
-agc.run()
-
-paths = natsort.natsorted(glob.glob(searchpath + "/*.pkl"))
-print(paths)
+filename = cli_args.file
 
-for i, path in enumerate(paths):
-    print(i, path)
-    adapt.load(path)
-    dpddata_after = adapt.get_predistorter()
+# No need to initialise a GlobalConfig since adapt only needs this one field
+class DummyConfig:
+    def __init__(self):
+        self.plot_location = None
 
-    coefs_am, coefs_pm = model.reset_coefs()
-    adapt.set_predistorter(("poly", coefs_am, coefs_pm))
-    print("Loaded configuration without pre-distortion")
+c = DummyConfig()
 
-    raw_input("Key for pre-distortion ")
-    adapt.set_predistorter(dpddata_after)
-    print("Pre-distortion done")
+adapt = Adapt.Adapt(c, port_rc, coef_path)
 
-    raw_input("Key for next ")
+print("Loading and applying DPD settings from {}".format(filename))
+adapt.load(filename)
 
 # The MIT License (MIT)
 #
diff --git a/dpd/dpd.ini b/dpd/dpd.ini
index 7e4bd5f..af5c2fb 100644
--- a/dpd/dpd.ini
+++ b/dpd/dpd.ini
@@ -18,7 +18,7 @@ gainmode=var
 rate=8192000
 
 # keep in mind that the DPDCE will set the digital gain through the RC!
-digital_gain=0.6
+digital_gain=0.01
 
 [firfilter]
 enabled=1
diff --git a/dpd/environment.yml b/dpd/environment.yml
deleted file mode 100644
index 8abedb2..0000000
--- a/dpd/environment.yml
+++ /dev/null
@@ -1,134 +0,0 @@
-name: dab
-channels:
-- jochym
-- defaults
-dependencies:
-- _nb_ext_conf=0.4.0=py27_1
-- anaconda-client=1.6.3=py27_0
-- backports=1.0=py27_0
-- backports_abc=0.5=py27_0
-- bleach=1.5.0=py27_0
-- cairo=1.12.18=6
-- clyent=1.2.2=py27_0
-- configparser=3.5.0=py27_0
-- cycler=0.10.0=py27_0
-- dbus=1.10.10=0
-- decorator=4.0.11=py27_0
-- entrypoints=0.2.3=py27_0
-- enum34=1.1.6=py27_0
-- expat=2.1.0=0
-- fontconfig=2.11.1=6
-- freetype=2.5.5=2
-- functools32=3.2.3.2=py27_0
-- get_terminal_size=1.0.0=py27_0
-- glib=2.50.2=1
-- gst-plugins-base=1.8.0=0
-- gstreamer=1.8.0=0
-- harfbuzz=0.9.39=1
-- html5lib=0.9999999=py27_0
-- icu=54.1=0
-- ipykernel=4.6.1=py27_0
-- ipython=5.3.0=py27_0
-- ipython_genutils=0.2.0=py27_0
-- ipywidgets=6.0.0=py27_0
-- jinja2=2.9.6=py27_0
-- jpeg=8d=2
-- jsonschema=2.6.0=py27_0
-- jupyter=1.0.0=py27_3
-- jupyter_client=5.1.0=py27_0
-- jupyter_console=5.1.0=py27_0
-- jupyter_core=4.3.0=py27_0
-- libffi=3.2.1=1
-- libgcc=5.2.0=0
-- libgfortran=3.0.0=1
-- libiconv=1.14=0
-- libpng=1.6.27=0
-- libsodium=1.0.10=0
-- libxcb=1.12=1
-- libxml2=2.9.4=0
-- markupsafe=0.23=py27_2
-- matplotlib=2.0.2=np112py27_0
-- mistune=0.7.4=py27_0
-- mkl=2017.0.1=0
-- natsort=5.0.3=py27_0
-- nb_anacondacloud=1.4.0=py27_0
-- nb_conda=2.2.0=py27_0
-- nb_conda_kernels=2.1.0=py27_0
-- nbconvert=5.2.1=py27_0
-- nbformat=4.3.0=py27_0
-- nbpresent=3.0.2=py27_0
-- notebook=5.0.0=py27_0
-- numpy=1.12.1=py27_0
-- openssl=1.0.2k=2
-- pandas=0.20.1=np112py27_0
-- pandocfilters=1.4.1=py27_0
-- pango=1.39.0=0
-- path.py=10.3.1=py27_0
-- pathlib2=2.3.0=py27_0
-- pcre=8.39=1
-- pexpect=4.2.1=py27_0
-- pickleshare=0.7.4=py27_0
-- pip=9.0.1=py27_1
-- pixman=0.32.6=0
-- plotly=2.0.9=py27_0
-- prompt_toolkit=1.0.14=py27_0
-- ptyprocess=0.5.2=py27_0
-- py2cairo=1.10.0=py27_2
-- pycairo=1.10.0=py27_0
-- pygments=2.2.0=py27_0
-- pyparsing=2.1.4=py27_0
-- pyqt=5.6.0=py27_2
-- python=2.7.13=0
-- python-dateutil=2.6.0=py27_0
-- pytz=2017.2=py27_0
-- pyyaml=3.12=py27_0
-- pyzmq=16.0.2=py27_0
-- qt=5.6.2=0
-- qtconsole=4.3.0=py27_0
-- readline=6.2=2
-- requests=2.14.2=py27_0
-- scandir=1.5=py27_0
-- scikit-learn=0.18.1=np112py27_1
-- scipy=0.19.0=np112py27_0
-- setuptools=27.2.0=py27_0
-- simplegeneric=0.8.1=py27_1
-- singledispatch=3.4.0.3=py27_0
-- sip=4.18=py27_0
-- six=1.10.0=py27_0
-- sqlite=3.13.0=0
-- ssl_match_hostname=3.4.0.2=py27_1
-- subprocess32=3.2.7=py27_0
-- terminado=0.6=py27_0
-- testpath=0.3.1=py27_0
-- tk=8.5.18=0
-- tornado=4.5.1=py27_0
-- tqdm=4.11.2=py27_0
-- traitlets=4.3.2=py27_0
-- wcwidth=0.1.7=py27_0
-- wheel=0.29.0=py27_0
-- widgetsnbextension=2.0.0=py27_0
-- yaml=0.1.6=0
-- zeromq=4.1.5=0
-- zlib=1.2.8=3
-- atk=2.8.0=0
-- gdk-pixbuf=2.28.2=0
-- gtk2=2.24.28=0
-- pygobject2=2.28.6=0
-- pygtk2=2.24.0=0
-- pip:
-  - backports-abc==0.5
-  - backports.shutil-get-terminal-size==1.0.0
-  - backports.ssl-match-hostname==3.4.0.2
-  - ipython-genutils==0.2.0
-  - jupyter-client==5.1.0
-  - jupyter-console==5.1.0
-  - jupyter-core==4.3.0
-  - multiprocessing==2.6.2.1
-  - nb-anacondacloud==1.4.0
-  - nb-conda==2.2.0
-  - nb-conda-kernels==2.1.0
-  - prompt-toolkit==1.0.14
-  - pynverse==0.1.4.4
-  - zmq==0.0.0
-prefix: /home/andreas/miniconda2/envs/dab
-
diff --git a/dpd/main.py b/dpd/main.py
index 49c0d1d..093f227 100755
--- a/dpd/main.py
+++ b/dpd/main.py
@@ -11,6 +11,7 @@
 This engine calculates and updates the parameter of the digital
 predistortion module of ODR-DabMod."""
 
+import sys
 import datetime
 import os
 import argparse
@@ -45,7 +46,7 @@ parser.add_argument('--digital_gain', default=0.6,
                     required=False,
                     type=float)
 parser.add_argument('--target_median', default=0.05,
-                    help='target_median',
+                    help='The target median for the RX and TX AGC',
                     required=False,
                     type=float)
 parser.add_argument('--samps', default='81920', type=int,
@@ -58,10 +59,14 @@ parser.add_argument('-L', '--lut',
                     help='Use lookup table instead of polynomial predistorter',
                     action="store_true")
 parser.add_argument('--plot',
-                    help='Enable all plots, to be more selective choose plots in Const.py',
+                    help='Enable all plots, to be more selective choose plots in GlobalConfig.py',
                     action="store_true")
 parser.add_argument('--name', default="", type=str,
                     help='Name of the logging directory')
+parser.add_argument('-r', '--reset', action="store_true",
+                    help='Reset the DPD settings to the defaults.')
+parser.add_argument('-s', '--status', action="store_true",
+                    help='Display the currently running DPD settings.')
 
 cli_args = parser.parse_args()
 
@@ -81,27 +86,36 @@ plot = cli_args.plot
 # Logging
 import logging
 
-dt = datetime.datetime.now().isoformat()
-logging_path = '/tmp/dpd_{}'.format(dt).replace('.', '_').replace(':', '-')
-if name:
-    logging_path += '_' + name
-os.makedirs(logging_path)
-logging.basicConfig(format='%(asctime)s - %(module)s - %(levelname)s - %(message)s',
-                    datefmt='%Y-%m-%d %H:%M:%S',
-                    filename='{}/dpd.log'.format(logging_path),
-                    filemode='w',
-                    level=logging.DEBUG)
-# also log up to INFO to console
-console = logging.StreamHandler()
-console.setLevel(logging.INFO)
-# set a format which is simpler for console use
-formatter = logging.Formatter('%(asctime)s - %(module)s - %(levelname)s - %(message)s')
-# tell the handler to use this format
-console.setFormatter(formatter)
-# add the handler to the root logger
-logging.getLogger('').addHandler(console)
-
-logging.info(cli_args)
+# Simple usage scenarios don't need to clutter /tmp
+if not (cli_args.status or cli_args.reset):
+    dt = datetime.datetime.now().isoformat()
+    logging_path = '/tmp/dpd_{}'.format(dt).replace('.', '_').replace(':', '-')
+    if name:
+        logging_path += '_' + name
+    print("Logs and plots written to {}".format(logging_path))
+    os.makedirs(logging_path)
+    logging.basicConfig(format='%(asctime)s - %(module)s - %(levelname)s - %(message)s',
+                        datefmt='%Y-%m-%d %H:%M:%S',
+                        filename='{}/dpd.log'.format(logging_path),
+                        filemode='w',
+                        level=logging.DEBUG)
+    # also log up to INFO to console
+    console = logging.StreamHandler()
+    console.setLevel(logging.INFO)
+    # set a format which is simpler for console use
+    formatter = logging.Formatter('%(asctime)s - %(module)s - %(levelname)s - %(message)s')
+    # tell the handler to use this format
+    console.setFormatter(formatter)
+    # add the handler to the root logger
+    logging.getLogger('').addHandler(console)
+else:
+    dt = datetime.datetime.now().isoformat()
+    logging.basicConfig(format='%(asctime)s - %(module)s - %(levelname)s - %(message)s',
+                        datefmt='%Y-%m-%d %H:%M:%S',
+                        level=logging.DEBUG)
+    logging_path = None
+
+logging.info("DPDCE starting up with options: {}".format(cli_args))
 
 import numpy as np
 import traceback
@@ -109,26 +123,38 @@ from src.Model import Lut, Poly
 import src.Heuristics as Heuristics
 from src.Measure import Measure
 from src.ExtractStatistic import ExtractStatistic
-from src.Adapt import Adapt
+from src.Adapt import Adapt, dpddata_to_str
 from src.RX_Agc import Agc
 from src.TX_Agc import TX_Agc
 from src.Symbol_align import Symbol_align
-from src.Const import Const
+from src.GlobalConfig import GlobalConfig
 from src.MER import MER
 from src.Measure_Shoulders import Measure_Shoulders
 
-c = Const(samplerate, target_median, plot)
+c = GlobalConfig(cli_args, logging_path)
 SA = Symbol_align(c)
 MER = MER(c)
 MS = Measure_Shoulders(c)
-meas = Measure(samplerate, port, num_req)
+meas = Measure(c, samplerate, port, num_req)
 extStat = ExtractStatistic(c)
-adapt = Adapt(port_rc, coef_path)
+adapt = Adapt(c, port_rc, coef_path)
+
+if cli_args.status:
+    txgain = adapt.get_txgain()
+    rxgain = adapt.get_rxgain()
+    digital_gain = adapt.get_digital_gain()
+    dpddata = dpddata_to_str(adapt.get_predistorter())
+
+    logging.info("ODR-DabMod currently running with TXGain {}, RXGain {}, digital gain {} and {}".format(
+        rxgain, rxgain, digital_gain, dpddata))
+    sys.exit(0)
 
 if cli_args.lut:
     model = Lut(c)
 else:
     model = Poly(c)
+
+# Models have the default settings on startup
 adapt.set_predistorter(model.get_dpd_data())
 adapt.set_digital_gain(digital_gain)
 
@@ -149,26 +175,13 @@ rx_gain = adapt.get_rxgain()
 digital_gain = adapt.get_digital_gain()
 
 dpddata = adapt.get_predistorter()
-if dpddata[0] == "poly":
-    coefs_am = dpddata[1]
-    coefs_pm = dpddata[2]
-    logging.info(
-        "TX gain {}, RX gain {}, dpd_coefs_am {},"
-        " dpd_coefs_pm {}, digital_gain {}".format(
-            tx_gain, rx_gain, coefs_am, coefs_pm, digital_gain
-        )
-    )
-elif dpddata[0] == "lut":
-    scalefactor = dpddata[1]
-    lut = dpddata[2]
-    logging.info(
-        "TX gain {}, RX gain {}, LUT scalefactor {},"
-        " LUT {}, digital_gain {}".format(
-            tx_gain, rx_gain, scalefactor, lut, digital_gain
-        )
-    )
-else:
-    logging.error("Unknown dpd data format {}".format(dpddata[0]))
+
+logging.info("TX gain {}, RX gain {}, digital_gain {}, {!s}".format(
+        tx_gain, rx_gain, digital_gain, dpddata_to_str(dpddata)))
+
+if cli_args.reset:
+    logging.info("DPD Settings were reset to default values.")
+    sys.exit(0)
 
 tx_agc = TX_Agc(adapt, c)
 
diff --git a/dpd/src/Adapt.py b/dpd/src/Adapt.py
index 7e19a2c..329ee20 100644
--- a/dpd/src/Adapt.py
+++ b/dpd/src/Adapt.py
@@ -16,8 +16,6 @@ import os
 import datetime
 import pickle
 
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 LUT_LEN = 32
 FORMAT_POLY = 1
 FORMAT_LUT = 2
@@ -44,6 +42,19 @@ def _write_lut_file(scalefactor, lut, path):
         f.write("{}\n{}\n".format(coef.real, coef.imag))
     f.close()
 
+def dpddata_to_str(dpddata):
+    if dpddata[0] == "poly":
+        coefs_am = dpddata[1]
+        coefs_pm = dpddata[2]
+        return "dpd_coefs_am {}, dpd_coefs_pm {}".format(
+                coefs_am, coefs_pm)
+    elif dpddata[0] == "lut":
+        scalefactor = dpddata[1]
+        lut = dpddata[2]
+        return "LUT scalefactor {}, LUT {}".format(
+                scalefactor, lut)
+    else:
+        raise ValueError("Unknown dpddata type {}".format(dpddata[0]))
 
 class Adapt:
     """Uses the ZMQ remote control to change parameters of the DabMod
@@ -55,8 +66,9 @@ class Adapt:
         ZMQ remote control.
     """
 
-    def __init__(self, port, coef_path):
+    def __init__(self, config, port, coef_path):
         logging.debug("Instantiate Adapt object")
+        self.c = config
         self.port = port
         self.coef_path = coef_path
         self.host = "localhost"
@@ -226,27 +238,30 @@ class Adapt:
         """Backup current settings to a file"""
         dt = datetime.datetime.now().isoformat()
         if path is None:
-            path = logging_path + "/" + dt + "_adapt.pkl"
+            if self.c.plot_location is not None:
+                path = self.c.plot_location + "/" + dt + "_adapt.pkl"
+            else:
+                raise Exception("Cannot dump Adapt without either plot_location or path set")
         d = {
             "txgain": self.get_txgain(),
             "rxgain": self.get_rxgain(),
             "digital_gain": self.get_digital_gain(),
             "predistorter": self.get_predistorter()
         }
-        with open(path, "w") as f:
+        with open(path, "wb") as f:
             pickle.dump(d, f)
 
         return path
 
     def load(self, path):
         """Restore settings from a file"""
-        with open(path, "r") as f:
+        with open(path, "rb") as f:
             d = pickle.load(f)
 
-        self.set_txgain(d["txgain"])
-        self.set_digital_gain(d["digital_gain"])
-        self.set_rxgain(d["rxgain"])
-        self.set_predistorter(d["predistorter"])
+            self.set_txgain(d["txgain"])
+            self.set_digital_gain(d["digital_gain"])
+            self.set_rxgain(d["rxgain"])
+            self.set_predistorter(d["predistorter"])
 
 # The MIT License (MIT)
 #
diff --git a/dpd/src/Dab_Util.py b/dpd/src/Dab_Util.py
index 2021f38..bc89a39 100644
--- a/dpd/src/Dab_Util.py
+++ b/dpd/src/Dab_Util.py
@@ -8,9 +8,6 @@
 import datetime
 import os
 import logging
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib
 
@@ -33,10 +30,11 @@ class Dab_Util:
      complex IQ samples of a DAB signal
      """
 
-    def __init__(self, sample_rate, plot=False):
+    def __init__(self, config, sample_rate, plot=False):
         """
         :param sample_rate: sample rate [sample/sec] to use for calculations
         """
+        self.c = config
         self.sample_rate = sample_rate
         self.dab_bandwidth = 1536000  # Bandwidth of a dab signal
         self.frame_ms = 96  # Duration of a Dab frame
@@ -53,9 +51,9 @@ class Dab_Util:
         off = sig_rec.shape[0]
         c = np.abs(signal.correlate(sig_orig, sig_rec))
 
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            corr_path = (logging_path + "/" + dt + "_tx_rx_corr.svg")
+            corr_path = self.c.plot_location + "/" + dt + "_tx_rx_corr.png"
             plt.plot(c, label="corr")
             plt.legend()
             plt.savefig(corr_path)
@@ -107,9 +105,9 @@ class Dab_Util:
         Returns an aligned version of sig_tx and sig_rx by cropping and subsample alignment
         """
 
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_sync_raw.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_sync_raw.png"
 
             fig, axs = plt.subplots(2)
             axs[0].plot(np.abs(sig_tx[:128]), label="TX Frame")
@@ -151,9 +149,9 @@ class Dab_Util:
             sig_tx = sig_tx[:-1]
             sig_rx = sig_rx[:-1]
 
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_sync_sample_aligned.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_sync_sample_aligned.png"
 
             fig, axs = plt.subplots(2)
             axs[0].plot(np.abs(sig_tx[:128]), label="TX Frame")
@@ -175,9 +173,9 @@ class Dab_Util:
 
         sig_rx = sa.subsample_align(sig_rx, sig_tx)
 
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_sync_subsample_aligned.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_sync_subsample_aligned.png"
 
             fig, axs = plt.subplots(2)
             axs[0].plot(np.abs(sig_tx[:128]), label="TX Frame")
@@ -199,9 +197,9 @@ class Dab_Util:
 
         sig_rx = pa.phase_align(sig_rx, sig_tx)
 
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_sync_phase_aligned.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_sync_phase_aligned.png"
 
             fig, axs = plt.subplots(2)
             axs[0].plot(np.abs(sig_tx[:128]), label="TX Frame")
diff --git a/dpd/src/ExtractStatistic.py b/dpd/src/ExtractStatistic.py
index d27cd77..639513a 100644
--- a/dpd/src/ExtractStatistic.py
+++ b/dpd/src/ExtractStatistic.py
@@ -8,13 +8,10 @@
 
 import numpy as np
 import matplotlib.pyplot as plt
-
 import datetime
 import os
 import logging
 
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 
 def _check_input_extract(tx_dpd, rx_received):
     # Check data type
@@ -64,10 +61,9 @@ class ExtractStatistic:
         self.plot = c.ES_plot
 
     def _plot_and_log(self, tx_values, rx_values, phase_diffs_values, phase_diffs_values_lists):
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
-
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_ExtractStatistic.png"
+            fig_path = self.c.plot_location + "/" + dt + "_ExtractStatistic.png"
             sub_rows = 3
             sub_cols = 1
             fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6))
diff --git a/dpd/src/Const.py b/dpd/src/GlobalConfig.py
index 6c9bafa..b84b9d7 100644
--- a/dpd/src/Const.py
+++ b/dpd/src/GlobalConfig.py
@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 #
-# DPD Computation Engine, constants.
+# DPD Computation Engine, constants and global configuration
 #
 # Source for DAB standard: etsi_EN_300_401_v010401p p145
 #
@@ -9,19 +9,20 @@
 
 import numpy as np
 
+class GlobalConfig:
+    def __init__(self, cli_args, plot_location):
+        self.sample_rate = cli_args.samplerate
+        assert self.sample_rate == 8192000  # By now only constants for 8192000
 
-class Const:
-    def __init__(self, sample_rate, target_median, plot):
-        assert sample_rate == 8192000  # By now only constants for 8192000
-        self.sample_rate = sample_rate
+        self.plot_location = plot_location
 
         # DAB frame
         # Time domain
-        self.T_F = sample_rate / 2048000 * 196608  # Transmission frame duration
-        self.T_NULL = sample_rate / 2048000 * 2656  # Null symbol duration
-        self.T_S = sample_rate / 2048000 * 2552  # Duration of OFDM symbols of indices l = 1, 2, 3,... L;
-        self.T_U = sample_rate / 2048000 * 2048  # Inverse of carrier spacing
-        self.T_C = sample_rate / 2048000 * 504  # Duration of cyclic prefix
+        self.T_F = self.sample_rate / 2048000 * 196608  # Transmission frame duration
+        self.T_NULL = self.sample_rate / 2048000 * 2656  # Null symbol duration
+        self.T_S = self.sample_rate / 2048000 * 2552  # Duration of OFDM symbols of indices l = 1, 2, 3,... L;
+        self.T_U = self.sample_rate / 2048000 * 2048  # Inverse of carrier spacing
+        self.T_C = self.sample_rate / 2048000 * 504  # Duration of cyclic prefix
 
         # Frequency Domain
         # example: np.delete(fft[3328:4865], 768)
@@ -34,10 +35,10 @@ class Const:
         # time per sample = 1 / sample_rate
         # frequency per bin = 1kHz
         # phase difference per sample offset = delta_t * 2 * pi * delta_freq
-        self.phase_offset_per_sample = 1. / sample_rate * 2 * np.pi * 1000
+        self.phase_offset_per_sample = 1. / self.sample_rate * 2 * np.pi * 1000
 
         # Constants for ExtractStatistic
-        self.ES_plot = plot
+        self.ES_plot = cli_args.plot
         self.ES_start = 0.0
         self.ES_end = 1.0
         self.ES_n_bins = 64  # Number of bins between ES_start and ES_end
@@ -45,7 +46,7 @@ class Const:
 
         # Constants for Measure_Shoulder
         self.MS_enable = False
-        self.MS_plot = plot
+        self.MS_plot = cli_args.plot
 
         meas_offset = 976  # Offset from center frequency to measure shoulder [kHz]
         meas_width = 100  # Size of frequency delta to measure shoulder [kHz]
@@ -63,24 +64,24 @@ class Const:
         self.MS_n_proc = 4
 
         # Constants for MER
-        self.MER_plot = plot
+        self.MER_plot = cli_args.plot
 
         # Constants for Model
-        self.MDL_plot = True or plot  # Override default
+        self.MDL_plot = cli_args.plot
 
         # Constants for Model_PM
         # Set all phase offsets to zero for TX amplitude < MPM_tx_min
         self.MPM_tx_min = 0.1
 
         # Constants for TX_Agc
-        self.TAGC_max_txgain = 89  # USRP specific
-        self.TAGC_tx_median_target = target_median
+        self.TAGC_max_txgain = 89  # USRP B200 specific
+        self.TAGC_tx_median_target = cli_args.target_median
         self.TAGC_tx_median_max = self.TAGC_tx_median_target * 1.4
         self.TAGC_tx_median_min = self.TAGC_tx_median_target / 1.4
 
         # Constants for RX_AGC
-        self.RAGC_min_rxgain = 25  # USRP specific
-        self.RAGC_rx_median_target = self.TAGC_tx_median_target
+        self.RAGC_min_rxgain = 25  # USRP B200 specific
+        self.RAGC_rx_median_target = cli_args.target_median
 
 # The MIT License (MIT)
 #
diff --git a/dpd/src/MER.py b/dpd/src/MER.py
index f186261..693058d 100644
--- a/dpd/src/MER.py
+++ b/dpd/src/MER.py
@@ -8,11 +8,6 @@
 import datetime
 import os
 import logging
-try:
-    logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-except:
-    logging_path = "/tmp/"
-
 import numpy as np
 import matplotlib
 matplotlib.use('agg')
@@ -76,9 +71,11 @@ class MER:
 
         spectrum = self._calc_spectrum(tx)
 
-        if self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_MER" + debug_name + ".svg"
+            fig_path = self.c.plot_location + "/" + dt + "_MER" + debug_name + ".png"
+        else:
+            fig_path = None
 
         MERs = []
         for i, (x, y) in enumerate(self._split_in_carrier(
@@ -103,7 +100,7 @@ class MER:
                 ylim = ax.get_ylim()
                 ax.set_ylim(ylim[0] - (ylim[1] - ylim[0]) * 0.1, ylim[1])
 
-        if self.plot:
+        if fig_path is not None:
             plt.tight_layout()
             plt.savefig(fig_path)
             plt.show()
diff --git a/dpd/src/Measure.py b/dpd/src/Measure.py
index d4b1d9e..b7423c6 100644
--- a/dpd/src/Measure.py
+++ b/dpd/src/Measure.py
@@ -11,14 +11,13 @@ import struct
 import numpy as np
 import src.Dab_Util as DU
 import os
-
 import logging
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
 
 class Measure:
     """Collect Measurement from DabMod"""
-    def __init__(self, samplerate, port, num_samples_to_request):
+    def __init__(self, config, samplerate, port, num_samples_to_request):
         logging.info("Instantiate Measure object")
+        self.c = config
         self.samplerate = samplerate
         self.sizeof_sample = 8 # complex floats
         self.port = port
@@ -106,7 +105,7 @@ class Measure:
         rx_median = np.median(np.abs(rxframe))
         rxframe = rxframe / rx_median * np.median(np.abs(txframe))
 
-        du = DU.Dab_Util(self.samplerate)
+        du = DU.Dab_Util(self.c, self.samplerate)
         txframe_aligned, rxframe_aligned = du.subsample_align(txframe, rxframe)
 
         logging.info(
diff --git a/dpd/src/Measure_Shoulders.py b/dpd/src/Measure_Shoulders.py
index c733dfd..fd90050 100644
--- a/dpd/src/Measure_Shoulders.py
+++ b/dpd/src/Measure_Shoulders.py
@@ -9,9 +9,6 @@ import datetime
 import os
 import logging
 import multiprocessing
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -79,8 +76,11 @@ class Measure_Shoulders:
         self.plot = c.MS_plot
 
     def _plot(self, signal):
+        if self.c.plot_location is None:
+            return
+
         dt = datetime.datetime.now().isoformat()
-        fig_path = logging_path + "/" + dt + "_sync_subsample_aligned.svg"
+        fig_path = self.c.plot_location + "/" + dt + "_sync_subsample_aligned.png"
 
         fft = calc_fft_db(signal, 100, self.c)
         peak, idxs_peak = _calc_peak(fft, self.c)
diff --git a/dpd/src/Model.py b/dpd/src/Model.py
index 67feeb6..b2c303f 100644
--- a/dpd/src/Model.py
+++ b/dpd/src/Model.py
@@ -2,6 +2,12 @@
 from src.Model_Poly import Poly
 from src.Model_Lut import Lut
 
+def select_model_from_dpddata(dpddata):
+    if dpddata[0] == 'lut':
+        return Lut
+    elif dpddata[0] == 'poly':
+        return Poly
+
 # The MIT License (MIT)
 #
 # Copyright (c) 2017 Andreas Steger
diff --git a/dpd/src/Model_AM.py b/dpd/src/Model_AM.py
index d7e880c..9800d83 100644
--- a/dpd/src/Model_AM.py
+++ b/dpd/src/Model_AM.py
@@ -8,9 +8,6 @@
 import datetime
 import os
 import logging
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -55,12 +52,12 @@ class Model_AM:
         self.plot = plot
 
     def _plot(self, tx_dpd, rx_received, coefs_am, coefs_am_new):
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             tx_range, rx_est = calc_line(coefs_am, 0, 0.6)
             tx_range_new, rx_est_new = calc_line(coefs_am_new, 0, 0.6)
 
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_Model_AM.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_Model_AM.png"
             sub_rows = 1
             sub_cols = 1
             fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6))
diff --git a/dpd/src/Model_Lut.py b/dpd/src/Model_Lut.py
index 6d4db52..e70fdb0 100644
--- a/dpd/src/Model_Lut.py
+++ b/dpd/src/Model_Lut.py
@@ -7,12 +7,8 @@
 
 import os
 import logging
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 
-
 class Lut:
     """Implements a model that calculates lookup table coefficients"""
 
diff --git a/dpd/src/Model_PM.py b/dpd/src/Model_PM.py
index d4f8c00..3aafea0 100644
--- a/dpd/src/Model_PM.py
+++ b/dpd/src/Model_PM.py
@@ -8,9 +8,6 @@
 import datetime
 import os
 import logging
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -41,12 +38,12 @@ class Model_PM:
         self.plot = plot
 
     def _plot(self, tx_dpd, phase_diff, coefs_pm, coefs_pm_new):
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             tx_range, phase_diff_est = self.calc_line(coefs_pm, 0, 0.6)
             tx_range_new, phase_diff_est_new = self.calc_line(coefs_pm_new, 0, 0.6)
 
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_Model_PM.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_Model_PM.png"
             sub_rows = 1
             sub_cols = 1
             fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6))
diff --git a/dpd/src/Model_Poly.py b/dpd/src/Model_Poly.py
index ff15941..cdfd319 100644
--- a/dpd/src/Model_Poly.py
+++ b/dpd/src/Model_Poly.py
@@ -7,9 +7,6 @@
 
 import os
 import logging
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 
 import src.Model_AM as Model_AM
@@ -54,13 +51,10 @@ class Poly:
         self.model_am = Model_AM.Model_AM(c, plot=self.plot)
         self.model_pm = Model_PM.Model_PM(c, plot=self.plot)
 
-        self.plot = c.MDL_plot
-
     def reset_coefs(self):
         self.coefs_am = np.zeros(5, dtype=np.float32)
         self.coefs_am[0] = 1
         self.coefs_pm = np.zeros(5, dtype=np.float32)
-        return self.coefs_am, self.coefs_pm
 
     def train(self, tx_abs, rx_abs, phase_diff, lr=None):
         """
diff --git a/dpd/src/RX_Agc.py b/dpd/src/RX_Agc.py
index 670fbbb..f778dee 100644
--- a/dpd/src/RX_Agc.py
+++ b/dpd/src/RX_Agc.py
@@ -9,8 +9,6 @@ import datetime
 import os
 import logging
 import time
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib
 matplotlib.use('agg')
@@ -70,11 +68,14 @@ class Agc:
     def plot_estimates(self):
         """Plots the estimate of for Max, Median, Mean for different
         number of samples."""
+        if self.c.plot_location is None:
+            return
+
         self.adapt.set_rxgain(self.min_rxgain)
         time.sleep(1)
 
         dt = datetime.datetime.now().isoformat()
-        fig_path = logging_path + "/" + dt + "_agc.svg"
+        fig_path = self.c.plot_location + "/" + dt + "_agc.png"
         fig, axs = plt.subplots(2, 2, figsize=(3*6,1*6))
         axs = axs.ravel()
 
diff --git a/dpd/src/Symbol_align.py b/dpd/src/Symbol_align.py
index d921f25..2a17a65 100644
--- a/dpd/src/Symbol_align.py
+++ b/dpd/src/Symbol_align.py
@@ -8,12 +8,6 @@
 import datetime
 import os
 import logging
-
-try:
-    logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-except:
-    logging_path = "/tmp/"
-
 import numpy as np
 import scipy
 import matplotlib
@@ -75,9 +69,9 @@ class Symbol_align:
 
         offset = peaks[np.argmin([tx_product_avg[peak] for peak in peaks])]
 
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_Symbol_align.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_Symbol_align.png"
 
             fig = plt.figure(figsize=(9, 9))
 
diff --git a/dpd/src/TX_Agc.py b/dpd/src/TX_Agc.py
index 3c804fa..309193d 100644
--- a/dpd/src/TX_Agc.py
+++ b/dpd/src/TX_Agc.py
@@ -9,9 +9,6 @@ import datetime
 import os
 import logging
 import time
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib
 
diff --git a/dpd/src/phase_align.py b/dpd/src/phase_align.py
index 68c216d..8654333 100644
--- a/dpd/src/phase_align.py
+++ b/dpd/src/phase_align.py
@@ -7,8 +7,6 @@
 import datetime
 import os
 import logging
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -24,9 +22,9 @@ def phase_align(sig, ref_sig, plot=False):
     real_diffs = np.cos(angle_diff)
     imag_diffs = np.sin(angle_diff)
 
-    if logging.getLogger().getEffectiveLevel() == logging.DEBUG and plot:
+    if plot and self.c.plot_location is not None:
         dt = datetime.datetime.now().isoformat()
-        fig_path = logging_path + "/" + dt + "_phase_align.svg"
+        fig_path = self.c.plot_location + "/" + dt + "_phase_align.png"
 
         plt.subplot(511)
         plt.hist(angle_diff, bins=60, label="Angle Diff")
diff --git a/dpd/src/subsample_align.py b/dpd/src/subsample_align.py
index 68f3591..20ae56b 100755
--- a/dpd/src/subsample_align.py
+++ b/dpd/src/subsample_align.py
@@ -7,14 +7,10 @@
 import datetime
 import logging
 import os
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 from scipy import optimize
 import matplotlib.pyplot as plt
 
-
 def gen_omega(length):
     if (length % 2) == 1:
         raise ValueError("Needs an even length array.")
@@ -32,7 +28,7 @@ def gen_omega(length):
     return omega
 
 
-def subsample_align(sig, ref_sig, plot=False):
+def subsample_align(sig, ref_sig, plot_location=None):
     """Do subsample alignment for sig relative to the reference signal
     ref_sig. The delay between the two must be less than sample
 
@@ -72,13 +68,13 @@ def subsample_align(sig, ref_sig, plot=False):
     if optim_result.success:
         best_tau = optim_result.x
 
-        if plot:
+        if plot_location is not None:
             corr = np.vectorize(correlate_for_delay)
             ixs = np.linspace(-1, 1, 100)
             taus = corr(ixs)
 
             dt = datetime.datetime.now().isoformat()
-            tau_path = (logging_path + "/" + dt + "_tau.svg")
+            tau_path = (plot_location + "/" + dt + "_tau.png")
             plt.plot(ixs, taus)
             plt.title("Subsample correlation, minimum is best: {}".format(best_tau))
             plt.savefig(tau_path)